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High performance computing on complex environments /
With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. This book provides recent research results in high-performance computing on complex environments, information on how to efficiently...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
John Wiley & Sons,
[2014]
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Jeannot, Emmanuel. | |
| 245 | 1 | 0 | |a High performance computing on complex environments / |c Emmanuel Jeannot, Julius Zilinskas. |
| 264 | 1 | |a Hoboken, New Jersey : |b John Wiley & Sons, |c [2014] | |
| 300 | |a 1 online resource (xxi, 395 pages) : |b illustrations | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record and CIP data provided by publisher. | |
| 520 | |a With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. This book provides recent research results in high-performance computing on complex environments, information on how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems, detailed studies on the impact of applying heterogeneous computing practices to real problems, and applications varying from remote sensing to tomography. Topics include: numerical analysis for heterogeneous and multicore systems; optimization of communication for high performance heterogeneous and hierarchical platforms; efficient exploitation of heterogeneous architectures, hybrid CPU+GPU, and distributed systems; energy awareness in high-performance computing; and applications of heterogeneous high-performance computing. -- |c Edited summary from book. | ||
| 505 | 0 | |6 880-01 |a Series; Title Page; Copyright; Dedication; Contributors; Preface; Part I: Introduction; Chapter 1: Summary of the Open European Network for High-Performance Computing in Complex Environments; 1.1 Introduction and Vision; 1.2 Scientific Organization; 1.3 Activities of The project; 1.4 Main Outcomes of the Action; 1.5 Contents of The Book; Acknowledgment; Part II: Numerical Analysis for Heterogeneous and Multicore Systems; Chapter 2: On the Impact of the Heterogeneous Multicore and Many-Core Platforms on Iterative Solution Methods and Preconditioning Techniques; 2.1 Introduction. | |
| 505 | 8 | |a 2.2 General Description of Iterative Methods and Preconditioning2.3 Preconditioning Techniques; 2.4 Defect-Correction Technique; 2.5 Multigrid Method; 2.6 Parallelization of Iterative Methods; 2.7 Heterogeneous Systems; 2.8 Maintenance and Portability; 2.9 Conclusion; Acknowledgments; References; Chapter 3: Efficient Numerical Solution of 2D Diffusion Equation on Multicore Computers; 3.1 Introduction; 3.2 Test Case; 3.3 Parallel Implementation; 3.4 Results; 3.5 Discussion; 3.6 Conclusion; Acknowledgment; References. | |
| 505 | 8 | |a Chapter 4: Parallel Algorithms for Parabolic Problems on Graphs in Neuroscience4.1 Introduction; 4.2 Formulation of the Discrete Model; 4.3 Parallel Algorithms; 4.4 Computational Results; 4.5 Conclusions; Acknowledgments; References; Part III: Communication and Storage Considerations in High-Performance Computing; Chapter 5: An Overview of Topology Mapping Algorithms and Techniques in High-Performance Computing; 5.1 Introduction; 5.2 General Overview; 5.3 Formalization of the Problem; 5.4 Algorithmic Strategies for Topology Mapping; 5.5 Mapping Enforcement Techniques; 5.6 Survey of Solutions. | |
| 505 | 8 | |a 5.7 Conclusion and Open ProblemsAcknowledgment; References; Chapter 6: Optimization of Collective Communication for Heterogeneous HPC Platforms; 6.1 Introduction; 6.2 Overview of Optimized Collectives and Topology-Aware Collectives; 6.3 Optimizations of Collectives on Homogeneous Clusters; 6.4 Heterogeneous Networks; 6.5 Topology- and Performance-Aware Collectives; 6.6 Topology as Input; 6.7 Performance as Input; 6.8 Non-MPI Collective Algorithms for Heterogeneous Networks; 6.9 Conclusion; Acknowledgments; References; Chapter 7: Effective Data Access Patterns on Massively Parallel Processors. | |
| 505 | 8 | |a 7.1 Introduction7.2 Architectural Details; 7.3 K-Model; 7.4 Parallel Prefix Sum; 7.5 Bitonic Sorting Networks; 7.6 Final Remarks; Acknowledgments; References; Chapter 8: Scalable Storage I/O Software for Blue Gene Architectures; 8.1 Introduction; 8.2 Blue Gene System Overview; 8.3 Design and Implementation; 8.4 Conclusions and Future Work; Acknowledgments; References; Part IV: Efficient Exploitation of Heterogeneous Architectures; Chapter 9: Fair Resource Sharing for Dynamic Scheduling of Workflows on Heterogeneous Systems; 9.1 Introduction; 9.2 Concurrent Workflow Scheduling. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a High performance computing. | |
| 650 | 6 | |a Superinformatique. | |
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| 700 | 1 | |a Žilinskas, J. |q (Julius), |d 1973- | |
| 758 | |i has work: |a High-performance computing on complex environments (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFPT8gyBhMcc7vHBcPMJKq |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Jeannot, Emmanuel. |t High performance computing on complex environments. |d Hoboken, New Jersey : John Wiley & Sons, [2014] |z 9781118712054 |w (DLC) 2013048363 |w (OCoLC)861477993 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1666528 |z Texto completo |
| 880 | 0 | 0 | |6 505-01/(S |g Machine generated contents note: |g 1. |t Summary of the Open European Network for High-Performance Computing in Complex Environments -- |g 1.1. |t Introduction and Vision / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.2. |t Scientific Organization / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.2.1. |t Scientific Focus / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.2.2. |t Working Groups / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.3. |t Activities of the Project / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.3.1. |t Spring Schools / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.3.2. |t International Workshops / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.3.3. |t Working Groups Meetings / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.3.4. |t Management Committee Meetings / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.3.5. |t Short-Term Scientific Missions / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.4. |t Main Outcomes of the Action / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 1.5. |t Contents of the Book / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |t Acknowledgment / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 2. |t On the Impact of the Heterogeneous Multicore and Many-Core Platforms on Iterative Solution Methods and Preconditioning Techniques / |r Julius [Ž]ilinskas / |r Emmanuel Jeannot -- |g 2.1. |t Introduction / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.2. |t General Description of Iterative Methods and Preconditioning / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.2.1. |t Basic Iterative Methods / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.2.2. |t Projection Methods: CG and GMRES / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.3. |t Preconditioning Techniques / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.4. |t Defect-Correction Technique / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.5. |t Multigrid Method / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.6. |t Parallelization of Iterative Methods / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.7. |t Heterogeneous Systems / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.7.1. |t Heterogeneous Computing / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.7.2. |t Algorithm Characteristics and Resource Utilization / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.7.3. |t Exposing Parallelism / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.7.4. |t Heterogeneity in Matrix Computation / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.7.5. |t Setup of Heterogeneous Iterative Solvers / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.8. |t Maintenance and Portability / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 2.9. |t Conclusion / |r Maya Neytcheva / |r Dimitar Lukarski -- |t Acknowledgments / |r Maya Neytcheva / |r Dimitar Lukarski -- |t References / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 3. |t Efficient Numerical Solution of 2D Diffusion Equation on Multicore Computers / |r Maya Neytcheva / |r Dimitar Lukarski -- |g 3.1. |t Introduction / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.2. |t Test Case / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.2.1. |t Governing Equations / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.2.2. |t Solution Procedure / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.3. |t Parallel Implementation / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.3.1. |t Intel PCM Library / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.3.2. |t OpenMP / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.4. |t Results / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.4.1. |t Results of Numerical Integration / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.4.2. |t Parallel Efficiency / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.5. |t Discussion / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 3.6. |t Conclusion / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |t Acknowledgment / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |t References / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 4. |t Parallel Algorithms for Parabolic Problems on Graphs in Neuroscience / |r Matja[ž] Depolli / |r Roman Trobec / |r Gregor Kosec -- |g 4.1. |t Introduction / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.2. |t Formulation of the Discrete Model / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.2.1. |t θ-Implicit Discrete Scheme / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.2.2. |t Predictor[--]Corrector Algorithm I / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.2.3. |t Predictor[--]Corrector Algorithm II / |r Natalija Tumanova / |r Raimondas Ciegis -- |g 4.3. |t Parallel Algorithms / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.3.1. |t Parallel θ-Implicit Algorithm / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.3.2. |t Parallel Predictor[--]Corrector Algorithm I / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.3.3. |t Parallel Predictor[--]Corrector Algorithm II / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.4. |t Computational Results / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.4.1. |t Experimental Comparison of Predictor[--]Corrector Algorithms / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.4.2. |t Numerical Experiment of Neuron Excitation / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 4.5. |t Conclusions / |r Raimondas Ciegis / |r Natalija Tumanova -- |t Acknowledgments / |r Natalija Tumanova / |r Raimondas Ciegis -- |t References / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 5. |t Overview of Topology Mapping Algorithms and Techniques in High-Performance Computing / |r Raimondas Ciegis / |r Natalija Tumanova -- |g 5.1. |t Introduction / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.2. |t General Overview / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.2.1. |t Key to Scalability: Data Locality / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.2.2. |t Data Locality Management in Parallel Programming Models / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.2.3. |t Virtual Topology: Definition and Characteristics / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.2.4. |t Understanding the Hardware / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.3. |t Formalization of the Problem / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.4. |t Algorithmic Strategies for Topology Mapping / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.4.1. |t Greedy Algorithm Variants / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.4.2. |t -Graph Partitioning / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.4.3. |t Schemes Based on Graph Similarity / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.4.4. |t Schemes Based on Subgraph Isomorphism / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.5. |t Mapping Enforcement Techniques / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.5.1. |t Resource Binding / |r Guillaume Mercier / |r Emmanuel Jeannot / |r Torsten Hoefler -- |g 5.5.2. |t Rank Reordering / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.5.3. |t Other Techniques / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.6. |t Survey of Solutions / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.6.1. |t Algorithmic Solutions / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.6.2. |t Existing Implementations / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 5.7. |t Conclusion and Open Problems / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |t Acknowledgment / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |t References / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot -- |g 6. |t Optimization of Collective Communication for Heterogeneous HPC Platforms / |r Torsten Hoefler / |r Guillaume Mercier / |r Emmanuel Jeannot. |
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